Topics

Featured in Development

Peter Alvaro talks about the reasons one should engage in language design and why many of us would (or should) do something so perverse as to design a language that no one will ever use. He shares some of the extreme and sometimes obnoxious opinions that guided his design process.

Featured in AI, ML & Data Engineering

Today on The InfoQ Podcast, Wes talks with Katharine Jarmul about privacy and fairness in machine learning algorithms. Jarul discusses what’s meant by Ethical Machine Learning and some things to consider when working towards achieving fairness. Jarmul is the co-founder at KIProtect a machine learning security and privacy firm based in Germany and is one of the three keynote speakers at QCon.ai.

Featured in Culture & Methods

Organizations struggle to scale their agility. While every organization is different, common patterns explain the major challenges that most organizations face: organizational design, trying to copy others, “one-size-fits-all” scaling, scaling in siloes, and neglecting engineering practices. This article explains why, what to do about it, and how the three leading scaling frameworks compare.

Amazon Web Services announces three new instance types

At it’s second re:invent conference Amazon Web Services announced three new instance types for its Elastic Compute Cloud (EC2) infrastructure as a service. I2 instances use solid state disk (SSD) to deliver high input/output performance, C3 instances tie each virtual CPU to a hardware hyper-thread for compute intensive workloads, and G2 instances offer Nvidia graphics processing units (GPUs) for 3D applications.

The largest I2 instances, i2.8xlarge, will combine 32 vCPUs, 244GiB of RAM and eight 720GB SSDs for non persistent instance storage. This top end instance is able to deliver 350,000 read input/output operations per second (IOPS) and 320,000 write IOPS. That level of performance is targeted at applications requiring high random I/O such as transactional systems and NoSQL databases. The family scales down to i2.large, which has a sixteenth of the capability of its largest sibling across all characteristics. The underlying hardware is based on Intel Xeon E5-2670v2 processors clocked at 2.5GHz. Netflix cloud architect Adrian Cockcroftcommented, ‘Any time someone publishes a cloud benchmark based on m1.small whack them with an i2.8xlarge until they go away’.

C3 instances are based on faster CPUs than the I2, using Xeon E5-2680v2 clocked at 2.8GHz, but they offer less RAM and smaller quantities of SSD storage. This instance family is aimed at compute intensive applications such as high performance computing (HPC) and analytics of large data sets using frameworks like Hadoop. In addition to a closer alignment of virtual CPU to hardware CPU, Amazon are also offering improved networking within their virtual private cloud (VPC) with greater throughput, lower latency and reduced jitter. To benefit from these networking improvements users must run machines with hardware virtual machine (HVM) networking enhancements. A number of Amazon machine images (AMIs) with baked in HVM support for C3 are offered to simplify the adoption process.

There is only one G2 instance type on offer, the g2.2xlarge. It offers 8 virtual CPUs (based on Intel’s older Sandy Bridge processors), 15GiB or RAM and 60GB of SSD storage. What makes it different from other instance types is the presence of an Nvidia GK104 GPU with 1536 cores and 4GB of video RAM. This can be used for graphics intensive applications such as 3D rendering and video encoding. Amazon take some pains to point out that the G2 isn’t intended for general purpose graphics processing unit (GPGPU) workloads as it lacks the double precision floating point and error correcting memory features of the CG1 instance type.

Once I2 instances become available, Amazon customers will have a choice between 28 different instance types across 7 different families. This is a somewhat bewildering array that will require careful analysis and selection, along with benchmarking where appropriate to ensure the right fit for a given application to the deployment environment. Amazon ‘recommend that you select the instance type that is most appropriate for your workload profile and scale’, and ‘change your instance type if your application's requirements change’. That’s potentially a lot of work for development and operations teams seeking to ensure that they have the right match. When combined with the variety of subscription models it’s becoming quite a challenge to ensure that a public cloud application is as economically efficient as possible.